Integrated Attribution Modeling for Content Campaign Conversions

Solution Overview

Problem

Conventional attribution models struggle to accurately track the influence of content campaigns on conversions due to the lack of individual-level data, leading to underestimation of their impact, as they are often placed in channels where data collection is challenging.

Innovation Solution

An analytics system integrates a media mix modeling model to determine attributions of content campaigns to intermediate events and a multi-touch attribution model to determine attributions of these events to conversions, effectively merging these models to generate a multi-stage attribution of content campaigns to conversions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional attribution models are used to track content campaigns, then the models can process available data, but they fail to accurately measure content campaign impact due to lack of individual-level data

Engineering Contradiction:

Improveattribution accuracyVSAvoidindividual-level data

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent introduces intermediate events as a mediator between content campaigns and conversions. These intermediate events serve as observable proxies that capture the influence of content campaigns at the individual level, enabling accurate attribution without requiring direct individual-level content campaign data. The intermediate events act as a bridge that translates unobservable content campaign effects into measurable individual-level outcomes.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent segments the attribution process into two distinct stages: first, modeling content campaign influence on intermediate events using aggregate data, and second, modeling the relationship between intermediate events and conversions using individual-level data. This segmentation allows each model to operate on appropriate data types while collectively achieving individual-level attribution accuracy.

Inventive Principle:

Principle #1Segmentation

2Productivity

If traditional media mix modeling is used to determine content campaign attribution, then the approach can work with aggregate data, but it underestimates content campaign impact by not capturing individual-level effects

Engineering Contradiction:

Improveattribution capabilityVSAvoidcampaign impact measurement

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent transitions from traditional two-dimensional attribution (campaign to conversion) to a three-dimensional framework by introducing intermediate events as a separate dimension. This allows the system to capture content campaign effects that operate through multiple pathways and timeframes, providing a more comprehensive and accurate measurement of campaign impact.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent introduces intermediate events as a mediator between content campaigns and conversions. These intermediate events serve as observable proxies that capture the influence of content campaigns at the individual level, enabling accurate attribution without requiring direct individual-level content campaign data. The intermediate events act as a bridge that translates unobservable content campaign effects into measurable individual-level outcomes.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If multi-touch attribution models are used, then they can track individual-level conversions, but they cannot effectively attribute content campaigns because content campaigns lack individual-level tracking data

Engineering Contradiction:

Improveconversion tracking accuracyVSAvoidcontent campaign data

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent introduces intermediate events as a mediator between content campaigns and conversions. These intermediate events serve as observable proxies that capture the influence of content campaigns at the individual level, enabling accurate attribution without requiring direct individual-level content campaign data. The intermediate events act as a bridge that translates unobservable content campaign effects into measurable individual-level outcomes.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent performs preliminary modeling of content campaign influence on intermediate events using aggregate data before conducting individual-level conversion attribution. This preliminary action creates a foundation that enables subsequent individual-level attribution by establishing the relationship between content campaigns and intermediate events at the population level, which then informs individual-level analysis.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260030652A1Model integration for content campaign attribution

Publication Date: 2026.01.29 ADOBE INC

AI summary

Some aspects relate to technologies providing a framework for integrating two machine learning models to determine an attribution of a content campaign to conversions. In accordance with some aspects, a first machine learning model (such as a media mix modeling model) generates a first attribution of a content campaign to intermediate events. A second machine learning model (such as a multi-touch attribution model) generates a second attribution of the intermediate events to conversions. An attribution of the content campaign to the conversions is determined as a function of the first attribution and the second attribution.